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Classification with abstention but without disparities

Classification with abstention but without disparities

Conference on Uncertainty in Artificial Intelligence (UAI), 2021
24 February 2021
Nicolas Schreuder
Evgenii Chzhen
    FaML
ArXiv (abs)PDFHTML

Papers citing "Classification with abstention but without disparities"

21 / 21 papers shown
Title
Abstain and Validate: A Dual-LLM Policy for Reducing Noise in Agentic Program Repair
Abstain and Validate: A Dual-LLM Policy for Reducing Noise in Agentic Program Repair
J. Cambronero
Michele Tufano
Sherry Shi
Renyao Wei
Grant Uy
Runxiang Cheng
Chin-Jung Liu
Shiying Pan
S. Chandra
Pat Rondon
72
1
0
03 Oct 2025
Unequal Uncertainty: Rethinking Algorithmic Interventions for Mitigating Discrimination from AI
Unequal Uncertainty: Rethinking Algorithmic Interventions for Mitigating Discrimination from AI
Holli Sargeant
Mackenzie Jorgensen
Arina Shah
Adrian Weller
Umang Bhatt
85
0
0
11 Aug 2025
Bayes-Optimal Fair Classification with Multiple Sensitive Features
Bayes-Optimal Fair Classification with Multiple Sensitive Features
Yi Yang
Yinghui Huang
Xiangyu Chang
FaML
467
0
0
01 May 2025
Interpretable and Fair Mechanisms for Abstaining Classifiers
Interpretable and Fair Mechanisms for Abstaining Classifiers
Daphne Lenders
Andrea Pugnana
Roberto Pellungrini
Toon Calders
D. Pedreschi
F. Giannotti
FaML
282
2
0
24 Mar 2025
Multi-Output Distributional Fairness via Post-Processing
Multi-Output Distributional Fairness via Post-Processing
Gang Li
Qihang Lin
Ayush Ghosh
Tianbao Yang
469
0
0
31 Aug 2024
Harnessing the Power of Vicinity-Informed Analysis for Classification
  under Covariate Shift
Harnessing the Power of Vicinity-Informed Analysis for Classification under Covariate Shift
Mitsuhiro Fujikawa
Yohei Akimoto
Jun Sakuma
Kazuto Fukuchi
173
0
0
27 May 2024
FairRR: Pre-Processing for Group Fairness through Randomized Response
FairRR: Pre-Processing for Group Fairness through Randomized ResponseInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Xianli Zeng
Joshua Ward
Guang Cheng
192
2
0
12 Mar 2024
Bandits with Abstention under Expert Advice
Bandits with Abstention under Expert Advice
Stephen Pasteris
Alberto Rumi
Maximilian Thiessen
Shota Saito
Atsushi Miyauchi
Fabio Vitale
Mark Herbster
138
3
0
22 Feb 2024
How Far Can Fairness Constraints Help Recover From Biased Data?
How Far Can Fairness Constraints Help Recover From Biased Data?International Conference on Machine Learning (ICML), 2023
Mohit Sharma
Amit Deshpande
FaML
232
5
0
16 Dec 2023
Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and
  Algorithms
Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and AlgorithmsInternational Conference on Algorithmic Learning Theory (ALT), 2023
Anqi Mao
M. Mohri
Yutao Zhong
230
36
0
23 Oct 2023
Theoretically Grounded Loss Functions and Algorithms for Score-Based
  Multi-Class Abstention
Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class AbstentionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Anqi Mao
M. Mohri
Yutao Zhong
185
33
0
23 Oct 2023
Fair Classifiers that Abstain without Harm
Fair Classifiers that Abstain without HarmInternational Conference on Learning Representations (ICLR), 2023
Tongxin Yin
Jean-François Ton
Ruocheng Guo
Yuanshun Yao
Mingyan Liu
Yang Liu
162
6
0
09 Oct 2023
Counterfactually Comparing Abstaining Classifiers
Counterfactually Comparing Abstaining ClassifiersNeural Information Processing Systems (NeurIPS), 2023
Yo Joong Choe
Aditya Gangrade
Aaditya Ramdas
272
1
0
17 May 2023
Fair learning with Wasserstein barycenters for non-decomposable
  performance measures
Fair learning with Wasserstein barycenters for non-decomposable performance measuresInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Solenne Gaucher
Nicolas Schreuder
Evgenii Chzhen
295
19
0
01 Sep 2022
Active learning algorithm through the lens of rejection arguments
Active learning algorithm through the lens of rejection argumentsMachine-mediated learning (ML), 2022
Christophe Denis
Mohamed Hebiri
Boris Ndjia Njike
Xavier Siebert
175
7
0
31 Aug 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey
Bias Mitigation for Machine Learning Classifiers: A Comprehensive SurveyACM Journal on Responsible Computing (JRC), 2022
Max Hort
Zhenpeng Chen
Jie M. Zhang
Mark Harman
Federica Sarro
FaMLAI4CE
297
233
0
14 Jul 2022
Fair Bayes-Optimal Classifiers Under Predictive Parity
Fair Bayes-Optimal Classifiers Under Predictive ParityNeural Information Processing Systems (NeurIPS), 2022
Xianli Zeng
Guang Cheng
Guang Cheng
FaML
182
18
0
15 May 2022
Bayes-Optimal Classifiers under Group Fairness
Bayes-Optimal Classifiers under Group Fairness
Xianli Zeng
Guang Cheng
Guang Cheng
FaML
345
24
0
20 Feb 2022
Fairness Indicators for Systematic Assessments of Visual Feature
  Extractors
Fairness Indicators for Systematic Assessments of Visual Feature ExtractorsConference on Fairness, Accountability and Transparency (FAccT), 2022
Priya Goyal
Adriana Romero Soriano
C. Hazirbas
Levent Sagun
Nicolas Usunier
EGVM
188
35
0
15 Feb 2022
Selective Regression Under Fairness Criteria
Selective Regression Under Fairness CriteriaInternational Conference on Machine Learning (ICML), 2021
Abhin Shah
Yuheng Bu
Joshua K. Lee
Subhro Das
Yikang Shen
P. Sattigeri
G. Wornell
273
31
0
28 Oct 2021
Error rate control for classification rules in multiclass mixture models
Error rate control for classification rules in multiclass mixture models
T. Mary-Huard
Vittorio Perduca
Gilles Blanchard
M. Martin-Magniette
159
6
0
29 Sep 2021
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